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Steiner, Peter M.; Kim, Yongnam – Society for Research on Educational Effectiveness, 2014
In contrast to randomized experiments, the estimation of unbiased treatment effects from observational data requires an analysis that conditions on all confounding covariates. Conditioning on covariates can be done via standard parametric regression techniques or nonparametric matching like propensity score (PS) matching. The regression or…
Descriptors: Observation, Research Methodology, Test Bias, Regression (Statistics)
Rahmatullah, Mamat – Higher Education Studies, 2016
In this study, the problem is limited factors relating to the learning effectiveness and teacher competence in improving the teacher performance. Therefore, this study will try to get explanations from some main issues which include the learning effectiveness issue, and teacher competence to increase teacher performance in Madrasah Tsanawiyah at…
Descriptors: Foreign Countries, Correlation, Statistical Inference, Statistics
Rakap, Salih; Snyder, Patricia; Pasia, Cathleen – Behavioral Disorders, 2014
Debate is occurring about which result interpretation aides focused on examining the experimental effect should be used in single-subject experimental research. In this study, we examined seven nonoverlap methods and compared results using each method to judgments of two visual analysts. The data sources for the present study were 36 studies…
Descriptors: Educational Research, Experiments, Research Problems, Research Methodology
Rosmaniar, Widhyanti; Marzuki, Shahril Charil bin Hj. – Higher Education Studies, 2016
The purpose of this study is to look closely at how aspects of instructional leadership, and organizational learning affect the quality of madrasah in improving the quality of graduate the state madrasah aliyah. The experiment was conducted using a quantitative approach with descriptive and inferential methods, in inferential methods used…
Descriptors: Principals, Instructional Leadership, Workplace Learning, Organizational Development
Osborne, Jason W.; Waters, Elaine – 2002
This Digest presents a discussion of the assumptions of multiple regression that is tailored to the practicing researcher. The focus is on the assumptions of multiple regression that are not robust to violation, and that researchers can deal with if violated. Assumptions of normality, linearity, reliability of measurement, and homoscedasticity are…
Descriptors: Error of Measurement, Nonparametric Statistics, Regression (Statistics), Reliability